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https://issues.apache.org/jira/browse/FLINK-1731?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hae Joon Lee updated FLINK-1731:
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Comment: was deleted
(was: To load input `Points` in fit function for `BreezeVector` we should use
input: DataSet[LebelVector]?
I implemented input dataset like trainingData = seq[DenseVector]
(DenseVector(-0.489811986685, 0.496883004904, -0.483860999346) ... )
In the case of K-means, datatype of `Centroids` can be LebelVector because it
has centroid number, but datatype of `Points` does not have to be LebelVector
in that it only has points as coordinates.)
> Add kMeans clustering algorithm to machine learning library
> -----------------------------------------------------------
>
> Key: FLINK-1731
> URL: https://issues.apache.org/jira/browse/FLINK-1731
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Assignee: Alexander Alexandrov
> Labels: ML
>
> The Flink repository already contains a kMeans implementation but it is not
> yet ported to the machine learning library. I assume that only the used data
> types have to be adapted and then it can be more or less directly moved to
> flink-ml.
> The kMeans++ [1] and the kMeans|| [2] algorithm constitute a better
> implementation because the improve the initial seeding phase to achieve near
> optimal clustering. It might be worthwhile to implement kMeans||.
> Resources:
> [1] http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf
> [2] http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf
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